The objectives of our research are (1) to determine how the health of the implanted cochlea, i.e. the biological conditions near the individual cochlear-implant electrodes, affects specific psychophysical and electrophysiological measures of electrical hearing; (2) to determine the relationships of these specific measures to speech recognition with the cochlear prosthesis; and (3) to use this information to increase the benefit that hearing impaired patients receive from their prostheses. The data from these studies can be used in two ways to improve speech recognition in cochlear implant users. First, based on animal work that will correlate the pattern of pathology with functional measures, we will provide audiologists with simple clinically applicable measures they can use to gain insight into the characteristics of the individual patient's cochlea and better identify and select the best stimulation sites for an individual patient's speech processor MAP. Second the data can help the biologist and the surgeon to determine the best anatomical targets for improving implant function through tissue-preservation and tissue-engineering strategies to make the impaired cochlea more receptive to cochlear implant stimulation. Our approach involves psychophysical and electrophysiological experiments in guinea pigs as well as psychophysical, electrophysiological and speech recognition studies in humans. We measure psychophysical performance, such as perceptual integration of pulse trains, and electrophysiological performance such as the rate at which evoked neural responses grow as a function of stimulus level. These measurements are made at individual stimulation sites in guinea pigs and humans. In guinea pigs we determine the specific anatomical features in the deaf or hearing-impaired cochlea that are correlated with these measures. In humans we determine the correlation of these same measures with speech recognition in quiet and in noisy backgrounds. We can then use these measures in humans to select the best stimulation sites for an individual subject's speech processor. This approach is supported by our previous studies showing that subjects usually perform better using a processor MAP with a subset of stimulation sites, carefully selected using appropriate functional measures, than they do with a processor that uses all available sites. The work proposed in this application will deepen our understanding of the mechanisms underlying variation in speech recognition performance across users of cochlear implants and serve as a guide for establishing and testing clinical procedures that will improve performance in individual patients.